Plasma kallikrein predicts primary graft dysfunction after heart transplant

J Heart Lung Transplant. 2021 Oct;40(10):1199-1211. doi: 10.1016/j.healun.2021.07.001. Epub 2021 Jul 10.

Abstract

Background: Primary graft dysfunction (PGD) is the leading cause of early mortality after heart transplant. Pre-transplant predictors of PGD remain elusive and its etiology remains unclear.

Methods: Microvesicles were isolated from 88 pre-transplant serum samples and underwent proteomic evaluation using TMT mass spectrometry. Monte Carlo cross validation (MCCV) was used to predict the occurrence of severe PGD after transplant using recipient pre-transplant clinical characteristics and serum microvesicle proteomic data. Putative biological functions and pathways were assessed using gene set enrichment analysis (GSEA) within the MCCV prediction methodology.

Results: Using our MCCV prediction methodology, decreased levels of plasma kallikrein (KLKB1), a critical regulator of the kinin-kallikrein system, was the most predictive factor identified for PGD (AUROC 0.6444 [0.6293, 0.6655]; odds 0.1959 [0.0592, 0.3663]. Furthermore, a predictive panel combining KLKB1 with inotrope therapy achieved peak performance (AUROC 0.7181 [0.7020, 0.7372]) across and within (AUROCs of 0.66-0.78) each cohort. A classifier utilizing KLKB1 and inotrope therapy outperforms existing composite scores by more than 50 percent. The diagnostic utility of the classifier was validated on 65 consecutive transplant patients, resulting in an AUROC of 0.71 and a negative predictive value of 0.92-0.96. Differential expression analysis revealed a enrichment in inflammatory and immune pathways prior to PGD.

Conclusions: Pre-transplant level of KLKB1 is a robust predictor of post-transplant PGD. The combination with pre-transplant inotrope therapy enhances the prediction of PGD compared to pre-transplant KLKB1 levels alone and the resulting classifier equation validates within a prospective validation cohort. Inflammation and immune pathway enrichment characterize the pre-transplant proteomic signature predictive of PGD.

Keywords: exosomes; machine learning; primary graft dysfunction.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Cardiomyopathies / blood*
  • Cardiomyopathies / surgery*
  • Cohort Studies
  • Extracellular Vesicles / metabolism
  • Female
  • Heart Transplantation / adverse effects*
  • Humans
  • Logistic Models
  • Machine Learning
  • Male
  • Middle Aged
  • Plasma Kallikrein / metabolism*
  • Predictive Value of Tests
  • Primary Graft Dysfunction / blood*
  • Primary Graft Dysfunction / etiology*
  • Proteomics
  • ROC Curve
  • Risk Factors

Substances

  • Plasma Kallikrein